涡轮泵振动参数与统计特征量的线性相关性分析

为了剔除冗余的振动参数和统计特征量，提高涡轮泵故障检测的实时能力，建立了线性相关性假设检验模型。利用该假设检验模型和某型液体火箭发动机的历史试车数据，检验了7路涡轮泵振动参数以及13种常用统计特征量的线性相关性，并分析了统计特征量对涡轮泵故障的敏感性和稳定性，以及涡轮泵振动数据的正态性。数据统计分析表明，大部分涡轮泵振动参数以及统计特征量显著线性相关，幅值统计特征量的故障敏感性弱，但稳定性强，而无量纲统计特征量的情况恰好相反，并且正常涡轮泵振动数据服从正态分布，而异常涡轮泵振动数据不再服从正态分布。据此，为涡轮泵故障检测选择了线性相关性弱，故障特征反映能力强的3路振动参数和3种统计特征量。

Linear correlation analysis of turbopump vibration parameters and statistical features

In order to abscind the redundant vibration parameters and statistical features, and enhance the real time capability of turbopump fault detection,the linear correlation hypothesis test model was built.With the help of this model and Liquid Rocket Engine(LRE) historical test data,the linear correlation hypothesis testing of 7 turbopump vibration parameters and that of 13 traditional statistical features were performed here.Then,the turbopump fault detection sensitivity and stability of statistical features and the normality of turbopump vibration data were also analyzed.The data statistic analysis results show that a majority of turbopump vibration and statistical features are evidently linear correlation;and the amplitude statis-tical features fault sensitivity is weak,but their fault stability is strong;while the dimensionless ones are just the contrary.What's more,the normal turbopump vibration data obey normal distribution;however the abnormal ones do not obey normal distribution anymore.So,3 vibration parameters and 3 statistical features,which are weak linear correlation and well reflect the faults characteristic,are selected for the LRE turbopump fault detection.